Modeling and Simulation of a Human Knee Exoskeleton's Assistive Strategies and Interaction

Abstract

Exoskeletons are increasingly used in rehabilitation and daily life in patients with motor disorders after neurological injuries. In this paper, a realistic human knee exoskeleton model based on a physical system was generated, a human–machine system was created in a musculoskeletal modeling software, and human–machine interactions based on different assistive strategies were simulated. The developed human–machine system makes it possible to compute torques, muscle impulse, contact forces, and interactive forces involved in simulated movements. Assistive strategies modeled as a rotational actuator, a simple pendulum model, and a damped pendulum model were applied to the knee exoskeleton during simulated normal and fast gait. We found that the rotational actuator–based assistive controller could reduce the user's required physiological knee extensor torque and muscle impulse by a small amount, which suggests that joint rotational direction should be considered when developing an assistive strategy. Compared to the simple pendulum model, the damped pendulum model based controller made little difference during swing, but further decreased the user's required knee flexor torque during late stance. The trade-off that we identified between interaction forces and physiological torque, of which muscle impulse is the main contributor, should be considered when designing controllers for a physical exoskeleton system. Detailed information at joint and muscle levels provided in this human–machine system can contribute to the controller design optimization of assistive exoskeletons for rehabilitation and movement assistance.

Are Functional Measures Sufficient to Capture Acceptance? A Qualitative Study on Lower Limb Exoskeleton Use for Older People

“…AT primarily provides help to perform activities of daily living (ADLs). The emergence of robotics plays a key role in the current trends to extend AT with personal robots, powered prosthetics, knee or ankle joint exoskeletons, motorized wheelchairs, and powered exoskeletons [21][22][23][24].…”

Weight Distribution of a Knee Exoskeleton Influences Muscle Activities During Movements

“…Jin et al, for instance, developed a treadmill-based platform to study the influence of exoskeletons' mass and inertia on muscle excitation and kinematics during gait [8]. Simulations are useful in this context to rapidly explore various exoskeleton mechanical designs, control strategies for assisting movements [16], and movements that are impractical to study in a lab environment, such as ramp walking. While muscle excitation is commonly measured experimentally using surface electromyography (EMG), they are limited to sensing excitation in superficial muscles.…”

An Integrated Dynamic Simulation Platform for Assistive Human-Robot Interaction: Application to Upper Limb Exosuit

“…Muscle strength augmentation for workers or soldiers [1], assistance to elderly generation in ADLs [2], muscle performance restoration in paraplegic patients [3], are few of the many applications of these devices. A review of existing devices and research approaches suggests that the exosuit design depends on some crucial developmental aspects: the user intention estimation, assistance torque estimation, and the comfort of force transmission [4][5][6][7]. As the experimental evaluation of these aspects on a physical setup can be tedious and accompanied by safety concerns, there is a requirement for the development of an integrated simulation framework where a virtual human model coupled with an external augmentation device can be tested and subsequently optimized.…”

“…In recent literature, Zhang et al employed an inverse dynamics and optimization-based technique using the Anybody Inc. software to observe the effects of different assistive strategies on the reduction in physiological torque and muscle impulse [7]. They utilized static optimization technique to calculate the muscle activations and the interaction forces at all the contact points between the exoskeleton and human body [7]. Although this approach is computationally efficient, the absence of a feedback correction term makes it sensitive to even slight errors in the predicted muscle activations.…”